Meet the Founders, Part 2: Homeworld Collective's Executive Director, Daniel Goodwin

(Recorded July 2024)

In this episode, Paul Reginato—co-founder of Homeworld Collective—turns the mic on Dan Goodwin, Homeworld’s co-founder and Executive Director, to explore his journey from near-failures in Boise, Idaho, to becoming a trailblazer in climate biotechnology.

Dan reflects on how his formative years at Harvey Mudd College and his time at Stanford under AI visionary Fei-Fei Li, coupled with his innovative stint at IDEO, ignited his passion for entrepreneurship and shaped his visionary approach. His story highlights the power of timing, collaboration, and resilience in transforming challenges into opportunities.

Together, they discuss the pressing hurdles facing climate biotech—from scalability issues to market forces that lag behind sectors like medical biotech and software development—and explore the critical need for centralized hubs of innovation. With a forward-thinking nonprofit approach, they discuss empowering practitioners to tackle the soluble problems at the intersection of climate and biotechnology. 

Tune in as Dan and Paul emphasize the importance of starting with well-defined problems and draw inspiration from initiatives like the COVID fast grants to accelerate high-quality research funding. Dan also shares invaluable advice for aspiring biotechnologists, sprinkling in insights from historical breakthroughs like Peter Mitchell’s ox-phosphorylation discovery. Through Homeworld Collective, they envision a future where collaboration and innovation drive exponential growth in climate biotech.

(00:00) Introduction to the Climate Biotech Podcast
(00:31) Meet the Founders: Dan Goodwin's Journey
(01:44) Dan's Early Life and Education
(03:29) Transition to Entrepreneurship and AI
(11:39) The Birth of Homeworld Collective
(14:23) Challenges in Climate Biotech
(17:33) Homeworld's Mission and Garden Grants
(29:33) Advice for Aspiring Biologists
(31:51) Dan's Favorite Science Factoids
(33:26) Future Vision for Homeworld Collective
(41:28) Closing Remarks and Thank You

Chapters

• 0:05 Journey Into Climate Biotech and Biology
• 11:57 Challenges in Climate Biotech and Business
• 18:24 Discovering and Solving Critical Problems
• 29:31 Building a Body of Work

Transcript

[00:00:00] Daniel Goodwin: Welcome to the climate biotech podcast, where we explore the most important problems at the intersection of climate and biology, and most importantly, how we can solve them. I'm Dan Goodwin, a technologist who spent years transitioning from software and neuroscience to a career in climate biotechnology.

As your host, I will interview our sector's most creative voices from scientists and entrepreneurs to policymakers and investors. 

[00:00:31] Paul Reginato: I'm Paul Reginato, one of the founders of Homeworld Collective, and today we're going to be doing things a little bit differently.

I'm going to be interviewing Dan Goodwin who is my co founder and the at Homeworld 

Collective. This is part of part two of a series of podcasts on get to know the founders of Homeworld so you can know who these people are that you're listening to interviewing different personalities in the world of climate biotech.

So in this series, we'll talk about our journeys into biology how we think about big problems in climate biotech, how we think about those at Homeworld, our dreams for the climate biotech community moving forward and an endless stream of cool biology factoids.

I'm really excited to be interviewing Dan my longtime friend who, I met right at the beginning of both of our PhDs when we were working in Ed Boyden's lab at MIT and getting into biological research together. We've been on a journey together for almost a decade now.

And discovering the world of climate biotech and the world of building community and discovering problems in climate biotech and founding Homeworld Collected Together. I'm really excited to help everybody get to know my friend Dan. Dan, why don't we start by just you telling us who you are and where you grew up and, the background for starting Homeworld.

Sure. 

[00:01:52] Dan: It's great to be here. My name is Dan Goodwin. I grew up in Boise, Idaho. To British immigrant parents I've got a pretty strict, no regrets policy in life, but there's definitely those times where I think, man, people think I'm so much smarter.

If I still had that British accent. Born in San Francisco, raised in Idaho since age nine, which is why I really own Idaho as a state I grew up at. And the, it's amazing to me, this journey, it doesn't make much sense when I look backward at it, but looking forward at it, I was just always, figuring stuff out and screwing up along the way.

I'm sure everyone who knew me in high school was appalled that I somehow ended up getting a PhD. It did only took me two tries. I was a total delinquent growing up. I was actually really close to being very below average. And I think that's part of the energy I bring into working hard now I got a lot of second chances.

I want to give those to others, but also want to make space to laugh at myself for being a total idiot. My attempt to get into science biology was thwarted a few times. I took a year off after high school. I went to live in Chile for a year. And in that time I got accepted to Harvey Mudd college.

And that was such a good fit for me because it was a very small, nerdy school. They had five majors when I was there. The fail out rate was about 10%. So the whole thing was just grinding people and showing people how good you can be. And I'm really glad I had that because I was very close to failing out.

So second time. Being, very very close to being below average. I turned it around in undergrad. I changed majors three times. I went from being an engineer to a math major, to a math bio major, and then back to an engineer. At the end of my college career, I got into entrepreneurship.

Entrepreneurship was a big failure the first time around I was living in a garage in Los Angeles after graduating undergrad and realized I needed more skills. So I enrolled at Stanford university for a PhD in neuroscience. I went to go work under Fei Fei Li who really, I think is what everyone would point to as one of the most pivotal figures in the AI boom. And I got to work under her.

I work in this windowless office in the Gates Computer Science building in 2009. And there's a lot of things that are important to that period of my life, which brought us to Homeworld and what we build now. That was the era where AI research really hit the big time. Not to disrespect people working before 2009, but what Feifei built specifically was the ImageNet challenge.

The ImageNet challenge was the first well built benchmark. Here's a big data set. Here's stuff that seems impossible at the time. Here's all these well labeled images, very clear tasks. Anybody can use our servers. Give us your best algorithms. And within two years, we had the deep learning revolution.

So that meant two things. One, every bit of research I did at that time was 100 percent useless. All the research I did in AI at that point has zero value in the world, except my own saltiness of knowing that if you work on the wrong problem or the wrong time, you might get a goose egg and that's fine.

But the other thing that I saw is that, wow, it can be amazing when fields come together, right? When you have those right catalysts, the right time. What that catalyst did to me at that time is it kicked me out of academia. Because while I was trying to work in Feifei's lab, all my energy and all my excitement was in the startup world, because outside of Feifei's creation of the ImageNet challenge was also AWS coming out and iPhone coming out and Facebook mini feed coming out and all these billion dollar companies and Y Combinator happening, and that energy sucked me in.

It was that or spend a year and a half cramming for the qualifying exams for Stanford. And I thought, forget this, I'm out. What really took me out of it was the opportunity to go be an entrepreneur in residence at IDEO. IDEO at the time, world leading global product design firm. And you'll hear this a lot in the way I operate and the way I try to bring playfulness and creativity in.

But for me, it was extremely humbling to go from someone who said, hi, I'm an engineer, I code stuff, to hi, I'm a product designer, let's play together and let's put sticky notes on walls and build toys for kids that was a fantastic opportunity in my career. And it was a credit to people giving me a second chance in some ways you could say I failed out and there's other people who saw something good in me and gave me a chance to step up.

What came out of that period was creating a company with my mentor and hero at the time. We built a company called MileIQ and in 2015, Microsoft acquired it. So I've seen that arc of kind of being in the right place at the right time, making the right bet. With the right team. And that ended up being a good outcome.

But it was also just, there was a lot of external factors around what we did as well as the team executing really well, and we'll come, we'll come to this more, but the, the punchline was when I was kind of now an adult, 20 something software entrepreneur, whatever you like trope you want to put me in.

And I was probably very average, like right in the middle of just imagine the Silicon Valley bro. 

And at that point, I was about 27, 28 at the time. And even then I had this realization that one day I'd be a dad. I wanted to pass on something heroic to my children. I didn't want it to be the story of I make iPhone apps for money and I can teach you to program too. I want it to be something, like what my dad inspires me and my mom inspires me.

And so I go back to the original intuition the excitement that took me into Stanford in the first place, which was the brain. And so the bet I made on my 29th birthday. was that I wanted to commit my life to work on the brain. So I also tried to convince myself I didn't need a PhD. If you want to work on the brain and you don't want a PhD, the option you have is go work in philanthropy, go work under a professor outside of an academic situation.

So I got to work under my hero, Sebastian Sung, who was one of the big names. We can trace every neuron create a full 3d map of the connectome. And I worked under him for a year and a half at the Simons foundation, which once again, amazing opportunity. I'm really grateful for that.

The biggest thing it gave me at that period of my life was the humility of always feeling like I was at the little kids table. I was surrounded by my heroes of neuroscience and I'm pretty smart. I work pretty hard. And when it really came down to the deep science of it, I felt like I was always a little kid's table at the dining room, like at the Thanksgiving feast.

So that was, I say this a lot to people who are trying to figure out their careers that I don't think everyone needs a PhD. But for the ego that I have and the kind of leader I want to be, at that point I made the investment. In the self architecture to one day be a leader in biotech.

And for that, I need the PhD and I had the options of doing more computational stuff with Sebastian or doing more experimental stuff with Ed Boyden. It was one of the hardest decisions ever made because I love Sebastian and he really is a hero and I'm so glad he was ultimately on my committee. I'm also really glad I got to work with Ed Boyden and we're going to always talk about some of the wisdom he imparted on us.

But the biggest thing I got when I started working in Ed's lab, and this is when you and I met in 2015, is Ed basically telling me, I don't care what you can do with some fancy computational models. I don't care what you can do, or what you think, or what math you can do. Until you've done any experiments, I don't care about your intuition.

I'm really glad he did because I was the quintessential arrogant programmer who thinks he can solve everything with code and then shows up and tries to do a wet lab experiment. And it's just absolutely garbage at it.

I even wrote an article on scientific American right before my PhD saying neuroscience needs hackers. Don't worry, everyone programmers are going to solve everything. And then I show up in my neuroscience PhD and I suck for two years. The first person who ever showed me how to use a pipette was Paul.

And it's really important because Paul was someone I really looked up to he had this bench filled with experiments. Doing many things at once and choosing a problem that was fundamentally interesting to me. Realizing that, hey, we always talked about DNA in terms of a 1D string of letters, but DNA actually sits in a 3D thing that's packed in a really tight little ball.

No one really understands the ball. Like we're going to figure that out. That I thought was really beautiful and was super emblematic of that shift I'd always come from my scientific work very abstract. Let's just program it all. Then you get into biology and it's actually super messy.

And what you think is good data from a microscope is very hard to get very hard to design experiments in the first place. There's just so much I learned in that period where this lands is that I realized near the end of my PhD that what brought me into do neuroscience was now being lit up with the excitement of synthetic biology.

That is I still love the brain and I'm still super fascinating. It's one of the most important things we can do with our lives. What I was finding was I was getting even more excited about what we can do with synthetic biology. And when you go back to this idea of trying to architect ourselves as heroes.

I didn't want to build a therapeutics company. I didn't feel any inspiration to go after another rare subtype of cancer and run a very athletic playbook to try to make a billion dollars. I found myself being really inspired by a lot of our conversations, Paul, of what can you do on a planetary scale with synthetic biology.

How can we get excited about synthetic biology's real potential of being atomically precise and infinitely scalable. To do that, you need to start operating outside of things that sit in the lab, outside of things that sit in the startup. And I think, the last thing I'll say about that is that I did have another one of my arcs of having a big second chance, 

I went in super arrogant and got smashed to bits, came out a little wiser on the other side, where I did think that I could go straight out of a PhD to create a climate biotech company, right? That was the thing like, hey, carbon capture is cool. Let's go. Or, hey, pollution is a really important problem.

Let's go. And what I realized is that to do stuff that's really hard in science, And also really uncertain business is a very hard proposition. And we'll talk more about that, but it was just one of those moments where you and I had been having a lot of conversations with the community. We'd seen, our conversations up on it had been hundreds of people.

And that was, I had this personal moment of, wow. If I'm struggling to create a company a lot of other people are probably struggling too, which is probably a signal on the field itself. Rather than the individuals inside it, and that's something worth fighting for, and that's what took us to Homeworld.

[00:11:44] Paul Reginato: That leads us well into the next question that I was going to ask you which is why do you think it's hard to work in climate biotech? And how did that lead you to wanting to start Homeworld Collective?

[00:11:57] Dan: One of my favorite lines that I've written in conversation, which was a result of a lot of conversations with you, and Nico McCarty, and Tony Kalesa, and all of our friends who, do fundamentally cutting edge work in Science . One of the favorite lines I ever wrote is that it's a great time to be a mouse with cancer.

And it's a super salty roast, but it's so true. If you are a mouse with cancer today, there are so many economic incentives for very smart humans to come up with drugs that are probably going to save your life and are not going to save the humans eventually, because it's going to translate poorly.

And it's a salty way to roast it, but it's a way of also appreciating why medical biotech works so well, which is that there's so much money on the other side of getting a drug for humans that you can price every step along the way. And when you go all the way back to the first experiments of, hey, we can affect this disease by changing this splice or changing this protein fold or inhibiting this function, that the field has now got to the spot where when you have a candidate like that and you publish your science paper, that academic frontier is now the industrial frontier.

And now income to venture capitalists who say, Hey, I like the way you drug this. I know how to price this. Let's get into a mouse. Let's get no monkey. Let's get into phase three, et cetera. That is a really good way of deploying capital, which makes it very easy. And I'm saying in big quotes, people are listening big quotes.

But it's very easy to deploy capital and medical biotech. It's also worth appreciating why it's easy, once again on quotes, to do stuff in the software industry, right? The reason that we were able to create our company in 2012 is that the iPhone platform had come out, meaning when I would write something that works on one iPhone, Apple would give me a platform to reach a hundred million people.

And when I designed an algorithm that sits on a server, once we got more users, then I would just get more servers and everything was really elastic. The scale was solved. The access to the market was solved. The stuff on accessing new users became very priceable, very salt. It's totally out of the context of this conversation, but a fun piece of trivia for that period is that Facebook ads doubled every year in their cost because they were so effective that even Facebook didn't know how much to charge people.

And a lot of that growth was the idea that people were figuring out just how you can scale software products. And just how incredibly scalable they are, which is why everyone tries to frame things as a software project. Anyway, you go then into climate biotech and you realize, oh, wow, this is a very hard space to work in.

It's very hard because you have hard science and you have hard business at the same time. By hard business, I mean what I'm talking about with software. It's hard to scale. It's hard to address new customers. It's hard to make sure that you're solving a big problem that if you solve it for one person, you can solve it for a thousand.

And then the science is how do you, if it works in one cell, how do you know it's going to work in the scale up to a thousand liters or a hundred thousand liters? And so when you look at those combined two flavors of heart at once, you get to a really difficult field to operate in. What we see today is that there's going to be pockets that work, 

the agriculture pocket of designing plants for human consumption is very well understood, and it's its own fiefdom. And then you go into mining, that sits in its own world with a lot of challenges and a lot of infrastructure. You go into things that are not as industrial like pollution management, and then it's going to be just the government and a whole sea of small contractors. We look at that and we say well, how do we make the space operate better? What has been missing in climate biotech, are those moments of catalysis or centralization, not of prescription, but of critical mass of humans.

The software industry, which you hear me talking about, had the centralization points of Feifei's ImageNet. Y Combinator, San Francisco's coding dens and all that stuff, right? In the genetic engineering world, you had Boston, the Doudna lab. You had the fun lab. You had all this CRISPR stuff happening.

All those problems were very specific. You had these amazing hotspots of very good capital allocators, everyone creating companies in a very small area. The question is how can we learn from what makes. Machine learning and computer science so scalable, how can we appreciate what makes medical biotech such a hot spot and what the recipes of success have been there.

And then we look at climate biotech and we say, okay, everybody agrees that there are frontier challenges that need to be solved. We need gigatons scale carbon capture. We know we need methane abatement. We know we can't have all these effed up chemicals in our body forever, we need more metals for the transition.

And at the same time, we know that the market forces trying to drive these changes aren't sufficient. And so you can either say we can do a top down challenge or just say let's have the government build a carbon capture institute and do that. Or you can say let's build the infrastructure to support bottom up by helping the best practitioners find what the problems they can work on and then support them with the resources, the infrastructure, the friends.

And so that is so once again, like why is climate biotech so hard to work in? Hard in business and hard in science, and it's been really diffuse across a bunch of fiefdoms. What we hope to do and the inspiration here is to have the audacity slash optimism that a non profit can function as a centralization point for people who want to work in climate biotech 

[00:17:32] Paul Reginato: amazing. So I wonder if you could tell us a little bit more about what Homeworld does so that people listening can understand Homeworld's activities, our theory of change and then, through that question, I'd love you to tell us a little bit about Garden Grants, which is the first big service that Homeworld Collective has created for the community.

And you've put a lot of really interesting ideas into that. So I'd love for you to just explain all that for us.

[00:18:02] Dan: Homeworld's theory of change is that it's possible to engineer the productivity of a whole field, and I think there's, it's both a very optimistic view, and an empowering view, and the question is that if you want to create exponential growth, you need a feedback mechanism, and an energy source. The power of our creative relationship is that you need to start with good problems. If you don't have a good problem, you're wasting your time. Richard Hamming has that great quote important problems lead to important work.

And I think that's true, right? Hamming was a very arrogant, old mathematician, but he was right on a lot of things. Sometimes you need that salty take of people work on unimportant problems, and you can see them just going off a cliff and wasting years of their life. This is Paul, what I always look to you for is like the rigor of breaking down a frontier challenge to what are the parts that actually matter.

 And I want to go a little deeper on this because when people come to us and they want to work on climate, a very common failure mode we see is people chasing their tail. One day they're like, Oh, methane is the most important thing. And they go 10 Google clicks deep and they ping us the next week.

And they say, Oh, you know what? Chemical production is the most important thing. And they go 10 Google clicks deep and get lost. Oh, actually, maybe carbon capture is the thing. We see people just lose months of their life. I feel really sensitive about this because I feel like this was me in 2020.

And maybe 2019. So I don't mean to judge unfairly on other people. I see this a lot. I've seen this a lot of myself too. So there's a very important service to do in the community. To rigorously help people find what the important subproblems are. And hopefully people that follow our work know that we're really specific with problem.

And we say problem with a capital P. Because we wanted to define a problem as something that a small team, say like the size of a lab, can pick up and run with, and they know exactly what they need to do to be impactful. We're not saying how they want to solve it, that's for people to figure out, but there's problems that are really important.

Once you get a community talking about problems, what do you do with it? That's not yet a feedback mechanism. The most important thing you do after you find good problems is you help people go act on those problems, right? To find good problems, you basically have to read papers and if we channel Ed Boyden, he would say, a day in the lab could save six months in the library or something like that.

[00:20:17] Paul Reginato: A lab can save six months in the library. And that's in response to the, because people will often say a day in the library can save six months in the lab, right? But it's like his cheeky inversion of that.

[00:20:27] Dan: I think it's true right, is that you know, , he teaches us to be salty about what you read in papers and be skeptical and maybe you can build intuition yourself. And so what we do is that after we help people find good problems and build a community culture around problems, we help people work on problems.

This goes to the garden grants you prompted me on I have to trace the, the origin of this to conversations with Tony Kalesa and Josh Moser back in 2020 and 2021 we were looking at the funding success of COVID FAST grants. And this is a little bit of a digression, but it's worth pointing out how much the science field is changing. In 2020 is everyone knows the pandemic was happening. The NIH wasn't moving fast enough. So a handful of philanthropists rallied around Tyler Cowen, a fantastic thinker and economist from George Mason University.

And they said, you know what? We can deploy capital in 24 hours. Just send us a two pager and we know enough whether we fund you or not. And they deployed 50 million like that and good research too. It created this there's a lot of words for this progress studies, meta science, whatever you want to talk about it, it started creating a really critical view on the way we do science now, because you have these big spikes of weight. 

The big splash made by the COVID Fast Grants is wait, you can fund 50 million in 24 hour turnaround and the work is good? Then what do you mean these what have we been doing with all these huge study circles and, year long programs to just make a decision 

Like it shook the whole science world. And to us, that was right when you and I are getting into climate biotech saying, wait, there's very little support for high risk biotech efforts towards a climate goal. We looked at the fast grants and thought, wait, that bridged for speed.

I think we've realized we can bridge for ambition, or we can bridge for things that don't yet have a funding home. When we try to fund to help people solve problems, it creates the opportunity to close that feedback. So homeworld can help the community surface really important problems to work on.

Then when it comes to funding those things, you can do it through a fast mechanism. In our case, it was, a few month turnaround, but also in a way that is. Inherently always focusing on problems and always inherently focusing on creating community through every process of a grant decision. On the outcome of that, you can feed the knowledge back in both on the new problems that are discovered and learnings from the way people are trying to solve it.

You now have ended up back where you started, which is okay, let's find some more problems. Moving forward there is a positive feedback loop between discovering problems and acting on problems. And we think that we can continue to channel the kinetic energy in through capital and also by helping create those nucleation sites through our road mapping.

And then we're also discovering as we help people that we fund what's blocking them. And what can Homeworld do is this lean organization that is rooted inside the practitioner community to help people solve their problems better. One problem area I think is very interesting. is how we can support with the metals transition and use biology's power of being atomically precise at the same time as being industrially robust.

And I couldn't think of much of a harder environment than a mine. And I'm personally really curious to continue going, to exploring this with the Homeworld team. To understand how we can find those important problems and also how we can unbundle, and I'm sorry for the mining people in the world when I call it a fiefdom, maybe there's a better way of saying it, but it's a very deep world where you've got a hundred thousand biologists who could be working on mining relevant problems and nobody has any perspective, 

unless, until you've gone to a mine, until you've poked around, until you have industrially relevant ores. And so I would love, this is the meta of yes, I'm very interested in how we get more lanthanides and how we get more lithium but I'm also very curious on the meta question of what does it take, you To help surface those important problems as I was just talking about, but in a really industrially deep world that I think wants to serve and helps us surface problems, at the same time, we're going to have to go through some red tape.

So I think as one category, I would just say that metals transition, so important, so interesting and also goes on a globally important trend of decentralization. I just think it's very important to build technologies need to build anyway, and the more we can decentralize, the less you have to ship stuff around the world for no reason, the more you can have standalone factories, the more we can be ambitious with making small machines that do more.

Metals, I think, would be one that I would just say, and I think one's pretty obvious. I think this is what people expect to work on, and it's going to be really exciting. Another topic that I think is still not yet consensus and is right on the border of what we would call climate biotech.

This idea of the small molecule pollutants in the world. You can start by saying, excess carbon dioxide is a small molecule waste from humanity. You can say the, all the methane we burp out, that's also, an undesired by product.

There's a very long tail of very weird small molecules being dumped out in the world. The best example is the story of the coho salmon up in, , Puget Sound. I'll tell the story because I think this helps us understand how little we know.

And so the story was, and in the, in the show notes, we absolutely need to give the researchers credit. 'cause I think the work is nothing short of heroic. But the short story is all the co-host salmon were dying in Puget Sound every time it rained. And nobody had any idea why the juvenile co-host salmon were dying.

All chemicals that go on the road. have been tested through the EPA. So there's not a toxicity thing that people originally worried about, yet something is making all these coho salmon die. The punchline is it was a preservative from car tires, washes down every time it rains into the river.

But it's not just that original preservative. It was a UV degraded version of that preservative, which then becomes toxic only to baby salmon. To do that work, if you read the science paper, they did a six step fractionation, which means that they, I can't even imagine the combinatorics of that experiment, to find the one piece of this sludge that was killing them, and then they could mass spec it and actually find what the chemical was it's a magnificent bit of sleuthing, but the question is, what else is there in the world that's messing with the biosphere?

That is not so targeted. The Coho Salmon story took that team three years and I'm, I haven't met them yet, so I don't mean to butcher their story, but it took them three years to find one molecule with a very acute harm. What do you do when the whole world is filled with microplastics, endocrine disrupting chemicals, heavy metals, pesticides, insecticides, every single one of us has Teflon precursors in us now.

At what point can we start taking that seriously? And the reason I think this is an interesting spot is that most of the work I see here is policy driven. Most things I see in this space are people saying, We're going to make a statistical argument about diseases and harms on a city scale or a county scale.

The wind blows in LA on this one way and kids do worse in school. It's an actual study. So these things are pretty well understood, but it's always trying to drive policy. And that doesn't inspire me. I don't think that works because if there are people out there actually trying to do bad and I don't like that mindset, but if there are, it's really easy to get around policy attempts.

But if we start getting the best of biotech, we start getting in the tool building mindset. Of saying, okay what does it mean to have perfect accountability of, hey, this pathogenesis in this person that caused this eventual harm can be traced down to most likely this original harm or this original chemical insult.

Or we can start saying, hey, we did a full blood test on you. These are the bad chemicals in your body. Here's what we're going to give you to get it out. Or you can start going into the forest and say, here's why the frogs aren't reproducing. Or here's why we have hermaphroditic polar bears in the Arctic, 

there's all these little opportunities, to put on more of a tool building and engineering head rather than let's be mad and shake our fist. I think what I would like to see in the pollution world eventually is this connection between environmental biotech, climate biotech, and human health.

And I think there's an opportunity to be rooted in the climate biotech sphere saying we can build biological tools for planetary scale health and benefit that affect the other spheres of the environment, and the human sphere. And so you can start with the heavy metals, I think it's a very natural place to start.

Mercury and lead is everywhere, has very known effects. We have ideas of how you can start clearing that out. And then I think you can start going more broad to one day finding the weird combinatorics of degradation products and what happens when you've got multiple bad chemicals in your body at once.

What I'd say is that I think we can start thinking about engineering biological resilience and that starts by tackling pollution from a tool builder's perspective. 

[00:29:21] Paul Reginato: Super cool ideas, Dan. And that's it. That's a pretty fresh one, at least for me. So we have only a few minutes left. I want to get through a few more questions. What's one bit of advice you have for junior people today getting into biology?

[00:29:39] Dan: a body of work. Super simple. Just make things and build things to show people. This is why I often support and encourage people to write more, because at least you can control words going on a page. I would encourage a body of work to include scientific work, engineering work, programming photography, art.

Really I'm in support of all of it. I would encourage people to focus on building things that they can share with the world. Build a body of work. Writing, I think, is the easiest to show the world how you're thinking at that day. I also think it's helpful to consider the expectations of where you are at that moment.

When I tell undergrads this, or I tell high school students this, I was like, go build a body of work. They'll say, I don't know what to say. I know people are going to think what I'm writing is dumb. And the answer is it probably is going to be dumb. But you're being judged as a high schooler or a college student.

And what people can see is effort. And it's much more important for you to build a body of work that expresses effort and growth than it is anything about perfection. This is what I learned almost too late in life when I went to the design world at age 26. I kind of wish I'd heard, somebody told me this at age 17, that high school Dan, you're being an idiot 99 percent of the time, but at least write something smart every so often.

And you'll be judged as a 17 year old, not as trying to be a Mr. Perfect. I would encourage people to just focus on building a body of work. A great example of this is a person came to me and he was a programmer trying to get into climate biotech. I told him I know you can program stuff.

But show me something that you're interested in by writing. He came back with a write up on a company cascade biocatalysts actually. It was really cool. I read it and I said, this to me reads like a smart programmer who is getting into biology, but does no much biology yet.

But it was super endearing because of this guy's clearly putting an effort, clearly trying. And then his next posts were clearly better. And so I think that is what people want is to see you build a body of work because that body of work is what you're going to transact and share when you're trying to open your next career opportunities.

[00:31:41] Paul Reginato: I think I could have used that bit of advice when I was younger as well. Dan, can you quickly tell us one favorite factoid you have about science?

[00:31:51] Dan: My favorite factoids about science are when we are totally humbled with how little we know. Learning that neurons can fire not just from axons to dendrites, but dendrites to axons as well. The endogenous cannabinoid system, super interesting. That one got me really excited.

How our cells are covered in these sugar polymers that we know nothing about, and we call it the glycocalyx, and it just looks like fuzz I think is beautiful and super interesting. But I think my favorite factoid, and this is more just reverence for a great moment in bio research, would be what's called the Oxfos Wars by Peter Mitchell who, when they were trying to discover all the chemical cascade to break down sugar and create ATP Everyone at the time was looking for this missing chemical metabolite that was the transaction of energy from the broken sugar to the ATP.

And nobody could find it. Everyone was assuming that the energy was somewhere in some chemical bond. This random dude was like, actually, no, we're transacting energy from chemical bonds into a chemical gradient. I think is one of the most beautiful stories of biology because he got kicked out of academia.

He got laughed out. He had to do his research in his home and they, had private wealth, later, he wins a Nobel prize for this. It's this great story of having the humility to realize that our mental models for biology are going to be insufficient. When we get sucked into our diagrams, they make us miss what might be there.

To me, the factoid, my favorite factoid of biology right now is the Oxfos Wars. I got that from reading The Vital Question by Nick Lane.

My last question. Looking forward what are your dreams for Homeworld Collective and how Homeworld can serve the climate biotech community? 

my dream for Homeworld is that we can demonstrate exponential growth in a field that really needs it. I want to see exponentially more money coming into the field. I want to see exponentially more researchers working in the field.

[00:33:46] Dan: I want to see exponentially more progress in terms of fundraising to teams that need it. I want to see more teams creating independent organizations. I want to see all these things increasing at an exponential rate. To do that, I think we're gonna have to think about kind of three dimensions, which is a two year and five years.

So we're going to think about short and long, but I also think we need to consider the larger field or what homeworld sits inside of. In the innovation ecosystem more broadly. I'll start with the two year. I think with the two year for homeworld is that we need to show that we have a repeatable mechanism for surfacing problems and funding teams doing that.

We had a really good first year and a half. I think our problem statement repository is coming together. People are beginning to get what we're talking about. I think the first round of garden grants. was successful. We have 16 amazing teams that it's as it's just so cool to get a chance to hang out with them and learn from them.

I think we're funding some of the best protein engineers in the world working on climate problems. And I think we need to show that we can do that again, each time bigger and better. So that's the core, of what the next two years are going to be, and what that's going to look is us doing more subsections of climate biotech.

So there's greenhouse gas removal, there's geobiotech and mining, as you and I have talked about. I'd love us to do a pollution relevant dive. There's a lot more work in those things as we work with the practitioner community to find what sub regions in climate biotech need the most impact or input from Homeworld Collective.

On the five year horizon, I want to show that Homeworld grows at the same exponential rate as the field we're supporting. And I think this is, on some hands, like on some ways this is obvious, right? Yes, sure, more money, more teammates, more science projects. That I think is going to be really important.

Inside the funding other teams, I also think it's us beginning to incubate projects ourselves. And I think it's a really exciting process. We are a research nonprofit. I want us to be one of many such teams doing this kind of work, to really talk about the five year vision for Homeworld, we need to talk about the five year vision for a lot of other teams like Homeworld.

So it's a very interesting time for research nonprofits to help build fields. And I've always kind of avoided saying this phrase, but just Recently I started leaning more into it is the idea of a field building org. So there are field building orgs for AI and bio. There are field building orgs for.

The progress studies movement there are field building orgs for quantum computing. So these are non profit teams that are coalescing people not on location like universities used to, but on domain topics, which is a beauty of the new hyperconnected world where we can just sit on zoom and go super deep.

Some fields are much better for distance collaboration than others. Seeing the peer group of these field building orgs grow, is going to be a big test and opportunity for the way we do science. I will always love universities. The reason I'm talking with an American accent, not a British accent, is that universities brought my family here.

I think we can do some of the things that universities do, but in a more distributed, lightweight way. I would love there to be, larger organizations, maybe like Homeworld in five years, but I also want a thriving ecosystem of smaller nonprofits. What I'm describing is the startup ecosystem my career started in.

I would love the way we do science to learn from why startups were so successful at both creating value in a dollar sense, but also creating careers. There are so many job titles that didn't exist 20 years ago before the startup ecosystem. I'm talking things about like growth hacker ops person, there's all these new technical team building roles that happen when you've got a community full of small teams operating with high individual agency.

But also loose collaborations and incentives to collaborate more. That's the startup ecosystem I grew up in and I love it. And I think we have all the raw materials to bring that into science, especially frontier science, like climate biotech. We started this conversation with you saying, Dan, why is it hard to work in climate biotech?

And I think it's because it's both hard in science and business. I think one of the ways that you can solve that is that if you can relax the constraint of maybe giving people more time to worry about the business risk and more steer into the science risk. That's what I think a larger community of research non profits could do.

That's one of the big optimisms for the next five years. 

So why have I been hesitant to use the word field building? The simple answer is You can't go to meta too soon.

[00:38:33] Dan: Otherwise you just lose people. And I'll say this in a really roundabout way. When I was in the early part of my career I would be so excited to get to go to conferences, and my company would pay for me or whatever, I'd show up and it's really fun to get sucked into these fancy rooms and people are talking really big, vague ideas.

And after a while, I realized it feels really cool to be in those rooms and you go 10 years later and nobody did anything, right. And I think it's because it's really easy to get sucked into vagueness that sounds cool, but then never actually do anything. So when I hesitate to use a word like field building, I hesitate because it speaks to a few people that are actually doing field building work.

It sounds vague and interesting to people that just like it for being vague and interesting, but then for the people that really need the field being built, I don't think it means anything. Center of Mass always has to be the practitioners doing the work. That's where Paul and I started.

Like I said, my mental model of Paul always is the guy with the lab bench full of 500 different versions of hydrogels. I don't say field building because it doesn't speak to our practice, like the practitioners. In the long run, I hope field building will be more of a term, but I don't think it matters that much because it's much more self referential.

What matters is that Homeworld's job is to serve the community and we serve the community by helping surface problems and helping fund solutions to those problems. That's it. As the field grows, we can find the language, maybe the community bubbles up something better than field building because right now that's funder language.

When we talk about our goal for Homeworld is and what our mission is, we are growing the field of climate biotech.

. Well, There's the one other side of vagueness that I think is a very recent tangible memory is that when we were setting off and we were telling funders that, hey, we think we can do scientific funding better than other people and we have a vision and we would say all these big words and we would say, look at fast grants and look, we're going to do community driven funding and look, we're going to have a conversation around problems and all that stuff.

Nobody got it. Except for the few people that really believed in us early days and were so grateful to our funders for that, for the most part, it was a lot of smiles and nods. Just because It was just too much language at once. It was too many new terms, too much vagueness.

And then, once we did the first garden grants. We can point to it and say, this is what it means to have discourse in public and have people put their problems publicly and people find clever, then you've got things for anyone to just look around and then they say, okay, I got it. It's no longer some fluffy, big meta idea. It's, Oh, that makes intuitive sense. Great. Let's do more of that. I'm hoping that as the track records develop for research, nonprofits that are building up the communities around them, that Then there will be a new language that everyone gets and naturally uses.

But until then, I don't want to force a stuffy word on everybody.

[00:41:28] Paul Reginato: All right, Dan. Thank you so much for this conversation. Even though we've been friends for, 10 years I learned more about you through this conversation and getting to interview you. This was really fun for me too. And I hope everyone listening enjoyed getting the chance to know you as well.

[00:41:43] Dan: Thank you so much, Paul. It's been a pleasure to be here. 

[00:41:46] Daniel Goodwin: Thank you so much for tuning into this episode of the climate biotech podcast. We hope this has been educational, inspirational, and fun for you as you navigate your own journey and bring the best of biotech into planetary scale solutions, we'll be back with another one soon.

And in the meantime, stay in touch with homeworld on LinkedIn, Twitter, or blue sky. Links are all in the show notes. Huge thanks to our producer, Dave Clark, and operations lead Paul Himmelstein for making these episodes happen.

Catch you on the next one.